Main menu

Tag Archives: Susan Etlinger

Post navigation

I’m in the bittersweet process of transitioning out of my role as industry analyst at Altimeter Group. I plan to remain with the company until early summer, finishing obligations and projects for some wonderful clients, including research and strategy work, as well as public speaking.

Then I’ll strike out and do something new. What, exactly, is still TBD.

I’m sharing this news for two reasons. First, transparency. At Adobe Summit last week, it was awkward to meet old friends and new acquaintances and answer the “what do you do?” question. Yes, I’m still at Altimeter, but one foot is inching toward the door.

I also want to signal my availability. I’m pleased to be in talks with a diverse list of organizations: brands, analyst firms, and agencies. I’m considering a variety of options, from remaining an analyst to putting my practitioner hat back on in a senior marketing role. I am also taking on client projects (advisory and thought leadership), as well as booking speaking engagements.

I’ve also been asked to join a number of advisory boards, an exciting prospect (unless I remain an analyst, in which case that’s a non-starter). I’m energized, daunted, nostalgic and sometimes wake up in the middle of the night, my head swimming with possibilities. It’s all good, and still very open-ended. I’m figuring this out while juggling a full workload and all the while maintaining my elite level frequent flyer status.

Working at Altimeter is one of the best jobs I ever had. I’m very proud of having produced a significant body of research on content marketing – more than any other researcher or analyst in the field – as well as my work in converged media. I’ve shared that knowledge in literally hundreds of keynotes and speeches on three continents, from major conferences to private events.

I’m also proud of my advisory and thought-leadership work with clients ranging from major banks, healthcare organizations, big-box retailers, and government agencies, to start-ups and non-profits. Recent clients include Home Depot, Adobe, Nestlé, Facebook, Gannett, Honeywell, The Federal Reserve Bank of New York, Fidelity, Wells Fargo, Anthem, American Express, IAB, as well as major ad and PR agencies.

I’m also honored to be frequently tapped for commentary by media outlets such as National Public Radio, The New York Times, the Wall Street Journal and the BBC when there’s breaking news about digital marketing or media.

And it will be my privilege to continue to contribute to the dialogue, the development, and the definitions of the disruptive technologies in marketing and media.

I’m also grateful. Charlene Li believed in me and took my career in an exciting new direction. Jeremiah Owyang supported me wholeheartedly and unconditionally as a fledgling analyst, and was an early co-author of a major piece of research. Brian Solis invited me to serve as editor of several of his reports, and to speak at his Pivot conference. The brilliant and talented Susan Etlinger is another co-author and collaborator. We published new research together just last week.

I couldn’t ask you to name a smarter, more supportive or inspirational group of colleagues. The research team has also been exceptional. If I look good at Altimeter, so much of that credit is due to crack researchers Christine Tran, Jessica Groopman and Jaimy Syzmanski (so many names I’m omitting….)

What’s next? I’ll keep you posted. Rest assured I’ll continue to research, write and speak under my own banner in the long term.

The foundation of content strategy is goals. Without knowing why content will be created and published — to what end, for whom, where, and how — content marketing is at best a spurious, ad hoc activity.

Yet when my colleague and partner-in-research Susan Etlinger and I sat down around a year ago to discuss the state of content measurement, we quickly realized growth in that sector is nowhere near commensurate with the overall growth of content marketing. This lead to research into what KPIs marketers should be working toward and measuring for in content, the subject of our latest research report titled Content Marketing Performance: A Framework to Measure Real Business Impact (free PDF download).

Content can indeed lift sales, but it can achieve so many more measurable, revenue-linked goals associated not only with marketing, but with other business areas, from product development to customer service. Our research outlines some of these KPIs, but goes further in that it helps marketers determine not just what to measure, but how to measure it.

Following, the key recommendations that resulted from our research:

Measurement must be the foundational principle of content strategy

In fact, there is no content strategy without measurement strategy. Before embarking on a content initiative, irrespective of medium or platform, it’s important to know what you want to achieve. Is it to drive more awareness? Build an audience? Encourage people to convert? Reduce call center expense by deflecting appropriate queries to a digital channel? Each requires different metrics — for content, yes, but also to calculate whether you have achieved your goal. Set and prioritize goals and desired outcomes, develop KPIs to track these, and measure and iterate constantly.

Every measurement strategy must focus on business outcome

Content metrics can be notoriously volume- or vanity-based, rather than outcome-based. This means that counting likes, shares, or organic reach in and of itself likely doesn’t demonstrate business value. To do that, you need to show a business outcome, using the compass in Figure 1. For example:

An increase in reach can show audience growth.

An increase in shares (preferably combined with other measures of engagement) can show engagement.

To understand whether a content strategy has affected brand reputation, you must have a benchmark, measure sentiment, and look at the before and after. It’s critical to have an analyst who can perform this correlation with an eye to other confounding factors. For example, a “viral” video may be immensely popular, but if there is a product recall, pricing change, or other factors, it may be difficult or even impossible to assess the impact on the business overall.

Know your metrics and your data

Some signals, like click-through rate, are clear and relatively easy to assess. Measuring sharing behavior requires that an analyst assess multiple platforms — Facebook, Twitter, Pinterest, Instagram, etc. — to define what “sharing” actually means. Compounding this issue is the fact that some of the most valuable data — for example, private Facebook data, or Snapchat data — are not available for privacy reasons. So analysts must take that into account as they assess impact and create defensible benchmarks as part of their process.

Be realistic about organizational capabilities and tools

Because content performance data comes in a variety of shapes and sizes, from various platforms, it often requires a great deal of manual intervention to analyze properly. This is simply a reality of the market today; content vendors often supply their own analytics dashboards, while social media tools also serve to measure content reach, resonance, and other (content-specific) outcomes.

It is not uncommon to require a mixture of web analytics, content measurement, marketing technology, and social media tools to assess the impact of content. As a result, content strategists should work with their analysts to develop a realistic (short-term) and aspirational (long-term) measurement strategy. Otherwise, content strategists and business leaders will inevitably become frustrated, while analysts will burn out from all the manual work needed to deliver reports.

Content has become pervasive. It fills websites, social media, advertising and collateral. It comprises words, images, audio-visual material, infographics and a host of other form factors. As media and channels proliferate, so too does content.

Yet, according to recent research I conducted, measuring content effectiveness remains the single most daunting task facing (content) marketers.

On my content marketing maturity model, applying measurement and strategy to content initiatives is the third of five levels of maturity.

But measuring only for sales and leads – or simply relying on volume or vanity metrics such as “likes” and “views” that contain little innate business value or meaning – undermines investments in time, media, employees, technology, and vendor relationships.

Content Metrics That Matter (Beyond Sales)

Together with my colleague Susan Etlinger, whose area of expertise is data, measurement and analytics, I’ve been researching content metrics that matter beyond those applied solely (and rather bluntly) to sales.

Clearly, sales matter. But as participation in content initiatives increases and permeates outward-facing and non-marketing divisions such as human resources, customer service and support, product groups, research and development, etc., which we call the Culture of Content, the metrics and KPIs that are applied to content correspondingly shift.

Non-marketing divisions don’t directly support sales but instead have their own success criteria. To encourage participation in content initiatives company-wide, content marketing must support these other departments’ goals that clearly, while not always in a manner that ties directly to sales, are of high value to the organization. Demonstrating this value only occurs through measurement.

In the course of our research we repeatedly found most organizations are at a loss for how to create and deliver useful, insightful and business-building content, and they’re equally puzzled about what KPIs to put in place to measure content benefits.

Content Strategy Is Fundamental

Content strategy would solve for this as strategy is, after all, founded on establishing goals and benchmarks for content marketing, then selecting the tools, processes and governance that will best achieve these goals. But since most companies still lack a documented content strategy, they also fall short in knowing what they want to (or can) measure. Additionally, they lack the tools and expertise to understand how to measure it.

Our recently-published research (free with registration) is a portfolio of case studies and examples of metrics applied in ways that illustrate the less-obvious benefits of content across a variety of scenarios: e.g. improved customer service, operational efficiencies, marketing optimization, etc. The reality is that content can support these goals, and all these goals can, in turn, correspond to monetary value.

It surprised both of us how much we had to struggle to find these case studies and examples, which underscores the underdeveloped state of content metrics.

Content Marketing Is Becoming As Integral To Business As Is Social

In 2011, Susan developed “A Framework for Social Analytics,” in which she introduced “The Social Media Measurement Compass.” We updated that graphic in our current report to apply to content. The intent then was to demonstrate the many ways in which social media could deliver value for the business.

Now, the market has evolved to a point where content — which resides not only in earned media channels, but also in owned and paid media — has become a separate entity that is integral to organizations’ ability to scale their communication efforts.

Beyond marketing and sales, content can play a critical role in improving brand health, augmenting the customer experience, reducing cost and risk, and many other goals of the business.

Here is the updated compass, illustrating the key value propositions of a well-crafted content strategy.

Each point represents an opportunity for business-centric measurement; that is, measurement that directly ties to business objectives and strategies. For example, operational efficiency metrics may refer to cost savings, risk, crisis management, or even productivity improvements.

These six points are by no means exhaustive, but provide a starting point for organizations eager to derive deeper insights from their content performance.

In many cases, the same “raw” metrics can be used as ingredients to answer many types of questions. In other cases, there are business or strategy-specific metrics that require data from other tools or sources, such as web analytics, business intelligence, market research, email marketing or CRM systems.

About a year ago, Rebecca Lieb and I had a series of conversations about the emerging need for analytics that would allow content and marketing professionals to evaluate the success of their content strategies. We discussed the predominance of “volume metrics” in content performance analysis, and the focus on linking content to conversion.

As we’ve both written before, that can be a significant challenge, for reasons having to do with attribution, browser complexity, and the complexity of human behavior in the buying cycle. So we wanted to take a look at some other ways that content marketers can gauge the success of their efforts.

The resulting report, “Content Marketing Performance: A Framework to Measure Real Business Impact,” is a look at six ways that content marketers can measure value. If that sounds familiar, it is: the social media measurement compass—which looks at brand health, marketing optimization, revenue generation, operational efficiency, customer experience and innovation—is relevant to content’s value as well.

You’ll notice that some of these case studies only include a few metrics; that is partly because some companies are reluctant to share their “secret sauce,” and because we are still in a very nascent state for content measurement. For that reason, we enriched the case studies with other metrics we’d recommend, so you can see how we might approach a measurement strategy to support specific business objectives.

We hope this report starts a conversation on content measurement, and will be happy to link to substantive posts that discuss the issues in detail. As always, thanks for reading, and we hope you find value in this document.

Content strategy and content marketing are where a great deal of my time and attention are focused as an analyst. Last month I discussed the trends in that sector that my research indicates will expand in 2015.

But wait — there’s more. Not only around content marketing, but around technology, channels, media and advertising, that bear watching this year, either because they are at the beginning of the disruption curve or about to hit its peak. Here’s what I, as well as many of my colleagues, will be watching this year with interest and curiosity.

Internet of things (IoT)

There’s plenty to be fascinated by in this emerging sector: wearables, smart devices, new equations of interoperability and integration, and of course lots and lots of new types of data. I’m also having many fascinating conversations with my colleague Jessica Groopman about her ongoing (and soon to be published) research on the IoT related to use cases for connected devices, and to a lesser extent, what kinds of content surround and are generated by the IoT. This represents the tip of a very big iceberg that will garner much attention this year — and for the next decade, at least.

The ethics of big data

Again, credit due to a colleague here. Drawn from her inspirational TED Talk, Susan Etlinger is researching an important and too often overlooked aspect of big data: its ethical implications. From data collection to communications (remember Target telling the father that his daughter was pregnant based on her buying pattern data?), Susan has pinpointed six broad categories, each with a host of specific areas, in which brands will be challenged with unprecedented ethical choices and policy issues. As more data stream in from areas such as the IoT, big questions will continue to swirl around big data.

Native advertising

In late 2013, I published the first research on the topic of native advertising. Native is still new and still disruptive, but this year we’ll see it normalize. Every major and reputable digital publisher and social media platform now offers native advertising products, and more formats are rapidly being developed. At the same time, policies, guidelines, ethics and technologies are not just springing up, but are also maturing. I predict that this year, native takes its place at the table as a critical and permanent component of digital marketing and advertising.

Channel convergence

A couple of years ago, together with then-colleague Jeremiah Owyang, I looked at how paid, owned and earned media are overlapping and combining to create new forms of media that, to consumers, are just…media. Distinctions between advertising, content, and social are blurring, if not dissolving. The same is beginning to happen with media channels. Is it radio? TV? Digital? Print? Is it projected or is it streaming, and do consumers care? (My hypothesis is that they don’t.) When all media can be consumed on all devices (large or small screens, phones, billboards, watches), what are the implications for media? Entertainment? Advertising and marketing? Mobile is TV is digital is audio is news is visual — portable, mutable, large and very, very small.

Those are the four trends I’ve got an eye on this year. What are yours? Let me know in the comments.

Over 30 Technologies Have Emerged, at a Faster Pace than Companies Can Digest.

If you think social was disruptive, it was really just the beginning. Altimeter’s research team recently convened for our annual research offsite and found over 30 disruptions and 15 trends that have emerged (see below for the full list in our Disruption Database). These disruptions and trends will affect consumers, business, government, the global economy; with accelerating speed, frequency and impact.

Four Major Business Disruptions Emerge – Business Leaders Must Prepare.

Out of these disruptions and trends, Altimeter identified four major themes that will be disruptive to business. Below is a preview of Altimeter’s four business disruption themes, with a definition and short description of each. In the coming weeks, we’ll publish a short report explaining these themes in more detail.

Everything Digital: An increasingly digital landscape – including data, devices, platforms and experiences – that will envelop consumers and businesses.

Everything Digital is the increasingly digital environment that depends on an evolving ecosystem of interoperable data, devices, platforms – experienced by people and business. It’s larger than the scope of Internet of Things, as it’s pervasive or ambient – not defined only by networked sensors and objects, but including capabilities such as airborne power grids or wireless power everywhere. Everything Digital serves as the backdrop for our next three themes.

Me-cosystem: The ecosystem that revolves around “me,” our data, and technologies that will deliver more relevant, useful, and engaging experiences using our data.

Wearable devices, near-field communications, or gesture-based recognition are just a few of the technologies that will make up an organic user interface for our lives, not just a single digital touchpoint. Digital experiences will be multiplied by new screen types, and virtual or augmented reality. Individuals who participate will benefit from contextualized digital experiences, in exchange for giving up personal data.

Digital Economies: New economic models caused by the digital democratization of production, distribution, and consumption.

Supply chains become consumption chains in this new economy as consumers become direct participants in production and distribution. Open source, social, and mobile platforms allow consumers to connect with each other, usurping traditional roles and relationships between buyers, sellers, and marketplaces. Do-it-yourself technologies such as 3D printing and replicators will accelerate this shift, while even currency becomes distributed and peer-to-peer-based. In this new economy, value shifts towards digital reputation and influence, digital goods and services; even data itself. The downside? An increasing divide between digital “haves” and the digital “have-nots.”

Dynamic Organization: In today’s digital landscape, dynamic organizations must develop new business models and ways of working to remain relevant, and viable.

Business leaders grapple with an onslaught of new technologies that result in shifting customer and employee expectations. It’s not enough to keep pace with change. To succeed, dynamic organizations must cultivate a culture, mindset, and infrastructure that enables flexibility and adaptability; the most pioneering will act as adaptive, mutable “ad-hocracies.”

Altimeter’s Disruption Database

Below are the 30 digital disruptions and 15 digital trends, which were used as the starting ground of our analysis.

Owned and earned media? That’s a whole other story. The metrics and the methods for measuring digital marketing are less exact, the platforms are newer, while the old rules and models don’t apply.

It’s been easier to groan about “lack of analytics expertise and/or resources,” “poor tools,” “unreliable data,” or “inconsistent analytical approaches” than to roll up collective organizational sleeves and really tackle the social media measurement problem. Yet with creativity, as well as hard metrics and defined business goals and strategies, organizations are not only measuring social media for ‘soft’ metrics such as brand sentiment, but also ‘hard’ data, such as revenue attribution.

While there’s admittedly no perfect measurement method, the study identifies no less than six models for measuring social media revenue impact, three “top-down,” and three “bottom-up.” The organizations that measure most effectively use a combination of these methods in concert, and the report provides a four-factor matrix to help determine which of the six methods apply, based on type of business, the product or service, media mix, and customer profile.

The media mix is of particular interest here, as my focus has been on the convergence of paid, owned, and earned media recently (the topic of my newest research report). Converged media models also require converging metrics, presenting the not inconsiderable challenge of applying findings and learnings from paid and owned, for example, into earned media. Or vice-versa, often in real or near-real time.

Like measuring social media ROI, these models are only just emerging. Measuring new media models is complex enough. The new necessity of measuring, learning, optimizing and applying data from one channel to another makes the challenge geometrically more formidable.